Doc contribution pr06

pandas/core/frame.py

@@ -322,7 +322,7 @@ class DataFrame(NDFrame):
         RangeIndex (0, 1, 2, ..., n) if no column labels are provided
     dtype : dtype, default None
         Data type to force. Only a single dtype is allowed. If None, infer
-    copy : boolean, default False
+    copy : bool, default False
         Copy data from inputs. Only affects DataFrame / 2d ndarray input
 
     See Also
@@ -1542,7 +1542,7 @@ def from_records(
         Parameters
         ----------
         data : ndarray (structured dtype), list of tuples, dict, or DataFrame
-        index : string, list of fields, array-like
+        index : str, list of fields, array-like
             Field of array to use as the index, alternately a specific set of
             input labels to use
         exclude : sequence, default None
@@ -1553,7 +1553,7 @@ def from_records(
             columns. Otherwise this argument indicates the order of the columns
             in the result (any names not found in the data will become all-NA
             columns)
-        coerce_float : boolean, default False
+        coerce_float : bool, default False
             Attempt to convert values of non-string, non-numeric objects (like
             decimal.Decimal) to floating point, useful for SQL result sets
         nrows : int, default None
@@ -3461,7 +3461,7 @@ def insert(self, loc, column, value, allow_duplicates=False):
         ----------
         loc : int
             Insertion index. Must verify 0 <= loc <= len(columns)
-        column : string, number, or hashable object
+        column : str, number, or hashable object
             label of the inserted column
         value : int, Series, or array-like
         allow_duplicates : bool, optional
@@ -4775,7 +4775,7 @@ def drop_duplicates(self, subset=None, keep="first", inplace=False):
             - ``first`` : Drop duplicates except for the first occurrence.
             - ``last`` : Drop duplicates except for the last occurrence.
             - False : Drop all duplicates.
-        inplace : boolean, default False
+        inplace : bool, default False
             Whether to drop duplicates in place or to return a copy
 
         Returns
@@ -5197,7 +5197,7 @@ def swaplevel(self, i=-2, j=-1, axis=0):
 
         Parameters
         ----------
-        i, j : int, string (can be mixed)
+        i, j : int, str (can be mixed)
             Level of index to be swapped. Can pass level name as string.
 
         Returns
@@ -5723,12 +5723,12 @@ def update(
 
         Parameters
         ----------%s
-        index : string or object, optional
+        index : str or object, optional
             Column to use to make new frame's index. If None, uses
             existing index.
-        columns : string or object
+        columns : str or object
             Column to use to make new frame's columns.
-        values : string, object or a list of the previous, optional
+        values : str, object or a list of the previous, optional
             Column(s) to use for populating new frame's values. If not
             specified, all remaining columns will be used and the result will
             have hierarchically indexed columns.
@@ -5850,14 +5850,14 @@ def pivot(self, index=None, columns=None, values=None):
             is function or list of functions
         fill_value : scalar, default None
             Value to replace missing values with
-        margins : boolean, default False
+        margins : bool, default False
             Add all row / columns (e.g. for subtotal / grand totals)
-        dropna : boolean, default True
+        dropna : bool, default True
             Do not include columns whose entries are all NaN
-        margins_name : string, default 'All'
+        margins_name : str, default 'All'
             Name of the row / column that will contain the totals
             when margins is True.
-        observed : boolean, default False
+        observed : bool, default False
             This only applies if any of the groupers are Categoricals.
             If True: only show observed values for categorical groupers.
             If False: show all values for categorical groupers.
@@ -6231,7 +6231,7 @@ def unstack(self, level=-1, fill_value=None):
 
         Parameters
         ----------
-        level : int, string, or list of these, default -1 (last level)
+        level : int, str, or list of these, default -1 (last level)
             Level(s) of index to unstack, can pass level name
         fill_value : replace NaN with this value if the unstack produces
             missing values
@@ -6305,7 +6305,7 @@ def unstack(self, level=-1, fill_value=None):
         ``frame.columns.name`` or 'variable'.
     value_name : scalar, default 'value'
         Name to use for the 'value' column.
-    col_level : int or string, optional
+    col_level : int or str, optional
         If columns are a MultiIndex then use this level to melt.
 
     Returns
@@ -6894,11 +6894,11 @@ def append(self, other, ignore_index=False, verify_integrity=False, sort=None):
         ----------
         other : DataFrame or Series/dict-like object, or list of these
             The data to append.
-        ignore_index : boolean, default False
+        ignore_index : bool, default False
             If True, do not use the index labels.
-        verify_integrity : boolean, default False
+        verify_integrity : bool, default False
             If True, raise ValueError on creating index with duplicates.
-        sort : boolean, default None
+        sort : bool, default None
             Sort columns if the columns of `self` and `other` are not aligned.
             The default sorting is deprecated and will change to not-sorting
             in a future version of pandas. Explicitly pass ``sort=True`` to
@@ -7940,7 +7940,7 @@ def idxmin(self, axis=0, skipna=True):
         ----------
         axis : {0 or 'index', 1 or 'columns'}, default 0
             0 or 'index' for row-wise, 1 or 'columns' for column-wise
-        skipna : boolean, default True
+        skipna : bool, default True
             Exclude NA/null values. If an entire row/column is NA, the result
             will be NA.
 
@@ -7977,7 +7977,7 @@ def idxmax(self, axis=0, skipna=True):
         ----------
         axis : {0 or 'index', 1 or 'columns'}, default 0
             0 or 'index' for row-wise, 1 or 'columns' for column-wise
-        skipna : boolean, default True
+        skipna : bool, default True
             Exclude NA/null values. If an entire row/column is NA, the result
             will be NA.
 

pandas/core/groupby/groupby.py

@@ -1032,7 +1032,7 @@ class GroupBy(_GroupBy):
         Most users should ignore this
     exclusions : array-like, optional
         List of columns to exclude
-    name : string
+    name : str
         Most users should ignore this
 
     Returns
@@ -1253,7 +1253,7 @@ def std(self, ddof=1, *args, **kwargs):
 
         Parameters
         ----------
-        ddof : integer, default 1
+        ddof : int, default 1
             degrees of freedom
 
         Returns
@@ -1276,7 +1276,7 @@ def var(self, ddof=1, *args, **kwargs):
 
         Parameters
         ----------
-        ddof : integer, default 1
+        ddof : int, default 1
             degrees of freedom
 
         Returns
@@ -1311,7 +1311,7 @@ def sem(self, ddof=1):
 
         Parameters
         ----------
-        ddof : integer, default 1
+        ddof : int, default 1
             degrees of freedom
 
         Returns
@@ -1623,7 +1623,7 @@ def pad(self, limit=None):
 
         Parameters
         ----------
-        limit : integer, optional
+        limit : int, optional
             limit of how many values to fill
 
         Returns
@@ -1649,7 +1649,7 @@ def backfill(self, limit=None):
 
         Parameters
         ----------
-        limit : integer, optional
+        limit : int, optional
             limit of how many values to fill
 
         Returns
@@ -2099,13 +2099,13 @@ def rank(
             * max: highest rank in group
             * first: ranks assigned in order they appear in the array
             * dense: like 'min', but rank always increases by 1 between groups
-        ascending : boolean, default True
+        ascending : bool, default True
             False for ranks by high (1) to low (N)
         na_option :  {'keep', 'top', 'bottom'}, default 'keep'
             * keep: leave NA values where they are
             * top: smallest rank if ascending
             * bottom: smallest rank if descending
-        pct : boolean, default False
+        pct : bool, default False
             Compute percentage rank of data within each group
         axis : int, default 0
             The axis of the object over which to compute the rank.
@@ -2313,7 +2313,7 @@ def shift(self, periods=1, freq=None, axis=0, fill_value=None):
 
         Parameters
         ----------
-        periods : integer, default 1
+        periods : int, default 1
             number of periods to shift
         freq : frequency string
         axis : axis to shift, default 0

pandas/core/groupby/grouper.py

@@ -48,17 +48,17 @@ class Grouper:
 
     Parameters
     ----------
-    key : string, defaults to None
+    key : str, defaults to None
         groupby key, which selects the grouping column of the target
     level : name/number, defaults to None
         the level for the target index
-    freq : string / frequency object, defaults to None
+    freq : str / frequency object, defaults to None
         This will groupby the specified frequency if the target selection
         (via key or level) is a datetime-like object. For full specification
         of available frequencies, please see `here
         <http://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`_.
     axis : number/name of the axis, defaults to 0
-    sort : boolean, default to False
+    sort : bool, default to False
         whether to sort the resulting labels
     closed : {'left' or 'right'}
         Closed end of interval. Only when `freq` parameter is passed.
@@ -69,7 +69,7 @@ class Grouper:
         If grouper is PeriodIndex and `freq` parameter is passed.
     base : int, default 0
         Only when `freq` parameter is passed.
-    loffset : string, DateOffset, timedelta object
+    loffset : str, DateOffset, timedelta object
         Only when `freq` parameter is passed.
 
     Returns

pandas/core/indexes/base.py

@@ -904,8 +904,8 @@ def repeat(self, repeats, axis=None):
 
         Parameters
         ----------
-        name : string, optional
-        deep : boolean, default False
+        name : str, optional
+        deep : bool, default False
         dtype : numpy dtype or pandas type
 
         Returns
@@ -1172,7 +1172,7 @@ def to_series(self, index=None, name=None):
         ----------
         index : Index, optional
             index of resulting Series. If None, defaults to original index
-        name : string, optional
+        name : str, optional
             name of resulting Series. If None, defaults to name of original
             index
 
@@ -1198,7 +1198,7 @@ def to_frame(self, index=True, name=None):
 
         Parameters
         ----------
-        index : boolean, default True
+        index : bool, default True
             Set the index of the returned DataFrame as the original Index.
 
         name : object, default None
@@ -1401,7 +1401,7 @@ def rename(self, name, inplace=False):
         ----------
         name : label or list of labels
             Name(s) to set.
-        inplace : boolean, default False
+        inplace : bool, default False
             Modifies the object directly, instead of creating a new Index or
             MultiIndex.
 
@@ -1494,7 +1494,7 @@ def sortlevel(self, level=None, ascending=True, sort_remaining=None):
 
         Parameters
         ----------
-        ascending : boolean, default True
+        ascending : bool, default True
             False to sort in descending order
 
         level, sort_remaining are compat parameters
@@ -3415,8 +3415,8 @@ def _reindex_non_unique(self, target):
         other : Index
         how : {'left', 'right', 'inner', 'outer'}
         level : int or level name, default None
-        return_indexers : boolean, default False
-        sort : boolean, default False
+        return_indexers : bool, default False
+        sort : bool, default False
             Sort the join keys lexicographically in the result Index. If False,
             the order of the join keys depends on the join type (how keyword)
 
@@ -3942,7 +3942,7 @@ def memory_usage(self, deep=False):
 
         Parameters
         ----------
-        cond : boolean array-like with the same length as self
+        cond : bool array-like with the same length as self
         other : scalar, or array-like
 
         Returns
@@ -4924,7 +4924,7 @@ def slice_indexer(self, start=None, end=None, step=None, kind=None):
         end : label, default None
             If None, defaults to the end
         step : int, default None
-        kind : string, default None
+        kind : str, default None
 
         Returns
         -------